Particle swarm optimization with an aging leader and challengers algorithm for optimal power flow problem with FACTS devices

被引:49
作者
Singh, Rudra Pratap [1 ]
Mukherjee, V. [2 ]
Ghoshar, S. P. [3 ]
机构
[1] Asansol Engn Coll, Dept Elect Engn, Asansol, W Bengal, India
[2] Indian Sch Mines, Dept Elect Engn, Dhanbad 826004, Bihar, India
[3] Natl Inst Technol, Dept Elect Engn, Durgapur, W Bengal, India
关键词
Aging; FACTS devices; Leader; Optimal power flow; Optimization; Particle swarm optimization;
D O I
10.1016/j.ijepes.2014.09.005
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Optimal power flow (OPF) problem is an optimization tool through which secure and economic operating conditions of power system is obtained. In this paper, particle swarm optimization (PSO) with an aging leader and challengers (ALC-PSO) is applied for the solution of the OFF problem of power system equipped with flexible ac transmission systems (FACTS). The two FACTS devices, namely, thyristor controlled series capacitor and thyristor controlled phase shifter are considered for this study. This study is implemented on modified IEEE 30-bus and IEEE 57-bus test power systems with four different objectives. The results presented in this paper demonstrate the potential of ALC-PSO algorithm and show its effectiveness for solving the OPF problem with FACTS devices over the other evolutionary optimization techniques surfaced in the recent state-of-the-art literature. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1185 / 1196
页数:12
相关论文
共 25 条
[1]   Optimal power flow using particle swarm optimization [J].
Abido, MA .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2002, 24 (07) :563-571
[2]   A Survey of Particle Swarm Optimization Applications in Electric Power Systems [J].
AlRashidi, M. R. ;
El-Hawary, M. E. .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2009, 13 (04) :913-918
[3]   OPTIMAL LOAD FLOW WITH STEADY-STATE SECURITY [J].
ALSAC, O ;
STOTT, B .
IEEE TRANSACTIONS ON POWER APPARATUS AND SYSTEMS, 1974, PA93 (03) :745-751
[4]  
[Anonymous], 2008, FACTS CONTROLLERS PO
[5]   Optimal power flow with FACTS devices using differential evolution [J].
Basu, M. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (02) :150-156
[6]   Multi-objective optimal power flow with FACTS devices [J].
Basu, M. .
ENERGY CONVERSION AND MANAGEMENT, 2011, 52 (02) :903-910
[7]   Solution of optimal power flow using nondominated sorting multi objective gravitational search algorithm [J].
Bhowmik, Arup Ratan ;
Chakraborty, A. K. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 62 :323-334
[8]   Multi-hive bee foraging algorithm for multi-objective optimal power flow considering the cost, loss, and emission [J].
Chen, Hanning ;
Bo, Ma Lian ;
Zhu, Yunlong .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 60 :203-220
[9]   Particle Swarm Optimization with an Aging Leader and Challengers [J].
Chen, Wei-Neng ;
Zhang, Jun ;
Lin, Ying ;
Chen, Ni ;
Zhan, Zhi-Hui ;
Chung, Henry Shu-Hung ;
Li, Yun ;
Shi, Yu-Hui .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2013, 17 (02) :241-258
[10]   Adaptive biogeography based predator-prey optimization technique for optimal power flow [J].
Christy, A. Ananthi ;
Raj, P. Ajay D. Vimal .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 62 :344-352